Technical Note: Fast two-dimensional GC-MS with thermal extraction for anhydro-sugars in fine aerosols

A fast two-dimensional gas chromatography (GC-MS) method that uses heart-cutting and thermal extraction (TE) and requires no chemical derivatization was developed for the determination of anhydro-sugars in fine aerosols. Evaluation of the TE-GC-GC-MS method shows high average relative accuracy (≥90%), reproducibility (≤10% relative standard deviation), detection limits of less than 3 ng/μL, and negligible carryover for levoglucosan, mannosan, and galactosan markers. TE-GC-GC-MS- and solvent extraction (SE)-GC-MS-measured levoglucosan concentrations correlate across several diverse types of biomass burning aerosols. Because the SE-GC-MS measurements were taken 8 years prior to the TE-GC-GC-MS ones, the stability of levoglucosan is established for quartz filter-collected biomass burning aerosol samples stored at ultra-low temperature (−50 °C). Levoglucosan concentrations (w/w) in aerosols collected following atmospheric dilution near open fires of varying intensity are similar to those in biomass burning aerosols produced in a laboratory enclosure. An average levoglucosan-mannosan-galactosan ratio of 15:2:1 is observed for these two aerosol sets. TE-GC-GC-MS analysis of atmospheric aerosols from the US and Africa produced levoglucosan concentrations (0.01–1.6 μg/m<sup>3</sup>) well within those reported for aerosols collected globally and examined using different analytical techniques (0.004–7.6 μg/m<sup>3</sup>). Further comparisons among techniques suggest that fast TE-GC-GC-MS is among the most sensitive, accurate, and precise methods for compound-specific quantification of anhydro-sugars. In addition, an approximately twofold increase in anhydro-sugar determination may be realized when combining TE with fast chromatography

Towards Emotion Recognition: A Persistent Entropy Application

Emotion recognition and classification is a very active area of research. In this paper, we present a first approach to emotion classification using persistent entropy and support vector machines. A topology-based model is applied to obtain a single real number from each raw signal. These data are used as input of a support vector machine to classify signals into 8 different emotions (calm, happy, sad, angry, fearful, disgust and surprised)

On predicting the outcomes of chemotherapy treatments in Breast cancer

Chemotherapy is the main treatment commonly used for treating cancer patients. However, chemotherapy usually causes side effects some of which can be severe. The effects depend on a variety of factors including the type of drugs used, dosage, length of treatment and patient characteristics. In this paper, we use a data extraction from an oncology department in Scotland with information on treatment cycles, recorded toxicity level, and various observations concerning breast cancer patients for three years. The objective of our paper is to compare several different techniques applied to the same data set to predict the toxicity outcome of the treatment. We use a Markov model, Hidden Markov model, Random Forest and Recurrent Neural Network in our comparison. Through analysis and evaluation of the performance of these techniques, we can determine which method is more suitable in different situations to assist the medical oncologist in real-time clinical practice. We discuss the context of our work more generally and further work.Postprin

NOTCH1 Signaling Promotes Human T-Cell Acute Lymphoblastic Leukemia Initiating Cell Regeneration in Supportive Niches

Leukemia initiating cells (LIC) contribute to therapeutic resistance through acquisition of mutations in signaling pathways, such as NOTCH1, that promote self-renewal and survival within supportive niches. Activating mutations in NOTCH1 occur commonly in T cell acute lymphoblastic leukemia (T-ALL) and have been implicated in therapeutic resistance. However, the cell type and context specific consequences of NOTCH1 activation, its role in human LIC regeneration, and sensitivity to NOTCH1 inhibition in hematopoietic microenvironments had not been elucidated.We established humanized bioluminescent T-ALL LIC mouse models transplanted with pediatric T-ALL samples that were sequenced for NOTCH1 and other common T-ALL mutations. In this study, CD34(+) cells from NOTCH1(Mutated) T-ALL samples had higher leukemic engraftment and serial transplantation capacity than NOTCH1(Wild-type) CD34(+) cells in hematopoietic niches, suggesting that self-renewing LIC were enriched within the NOTCH1(Mutated) CD34(+) fraction. Humanized NOTCH1 monoclonal antibody treatment reduced LIC survival and self-renewal in NOTCH1(Mutated) T-ALL LIC-engrafted mice and resulted in depletion of CD34(+)CD2(+)CD7(+) cells that harbor serial transplantation capacity.These results reveal a functional hierarchy within the LIC population based on NOTCH1 activation, which renders LIC susceptible to targeted NOTCH1 inhibition and highlights the utility of NOTCH1 antibody targeting as a key component of malignant stem cell eradication strategies

Viabilidade técnica e econômica do uso de diferentes níveis de grãos secos de destilaria com solúveis (Zea Mays L.) em borregas terminadas em confinamento

Avaliou-se a viabilidade da utilização de rações contendo diferentes níveis de grãos secos de destilaria com solúveis - GSDS (0, 8, 16 e 24%) em borregas confinadas. As rações continham 65% de volumoso (silagem de milho) e 35% de concentrado (grão de milho moído, farelo de soja, grãos secos de destilaria com solúveis e ureia). Foram utilizadas 16 borregas sem raça definida, com peso corporal (PC) inicial de 23,8 ± 1,5 kg, confinadas por 75 dias. Foi utilizado delineamento experimental inteiramente casualizados com quatro tratamentos. Os dados de consumo MS e ganho médio diário (GMD) das borregas alimentadas com os diferentes tratamentos foram submetidos à análise de variância e as diferenças obtidas foram analisadas por equação de regressão a 5% de significância. Os diferentes níveis de GSDS não alteraram o GMD das cordeiras em confinamento. Pela simulação técnica econômica, a diferença obtida no valor da receita total por carcaça das borregas foi de R$26,93 a mais para a ração a base de 16$ 5,67 a menos em relação à ração com 0% de GSDS. Foi verificado que as borregas alimentadas com os diferentes níveis de GSDS apresentaram uma receita de R$18,00 kg/carcaça, o que proporcionou uma diferença de R$ 2.693,00 na receita total entre as rações contendo 16 e 0% de GSDS para um módulo de 100 animais. A diferença do valor da receita total foi reflexo do maior peso da carcaça quente de 11,4% para a ração com 16% GSDS em relação à com 0% GSDS. A ração com 16% de GSDS apresentou um custo de R$ 1,48/kg menor em relação à ração com 0% de GSDS. Além disso, a ração com 16% de GSDS apresentou receita líquida total de 98,7% maior em relação à ração com 0% de GSDS. O grão seco de destilaria com solúveis pode ser inserido na dieta de borregas em terminação em até 24% da ração total sem alterar o desempenho animal, e ao considerar a simulação econômica a utilização de 16% de inclusão de GSDS apresenta maior lucratividade

Diversity of isoprene-degrading bacteria in phyllosphere and soil communities from a high isoprene-emitting environment: a Malaysian oil palm plantation

Background: Isoprene is the most abundantly produced biogenic volatile organic compound (BVOC) on Earth, with annual global emissions almost equal to those of methane. Despite its importance in atmospheric chemistry and climate, little is known about the biological degradation of isoprene in the environment. The largest source of isoprene is terrestrial plants, and oil palms, the cultivation of which is expanding rapidly, are among the highest isoprene-producing trees. Results: DNA stable isotope probing (DNA-SIP) to study the microbial isoprene-degrading community associated with oil palm trees revealed novel genera of isoprene-utilising bacteria including Novosphingobium, Pelomonas, Rhodoblastus, Sphingomonas and Zoogloea in both oil palm soils and on leaves. Amplicon sequencing of isoA genes, which encode the α-subunit of the isoprene monooxygenase (IsoMO), a key enzyme in isoprene metabolism, confirmed that oil palm trees harbour a novel diversity of isoA sequences. In addition, metagenome assembled genomes (MAGs) were reconstructed from oil palm soil and leaf metagenomes and putative isoprene degradation genes were identified. Analysis of unenriched metagenomes showed that isoA-containing bacteria are more abundant in soils than in the oil palm phyllosphere. Conclusion: This study greatly expands the known diversity of bacteria that can metabolise isoprene and contributes to a better understanding of the biological degradation of this important but neglected climate-active gas

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0\u20135 and 5\u201315 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10\ub0C (mean = 3.0 \ub1 2.1\ub0C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 \ub1 2.3\ub0C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler ( 120.7 \ub1 2.3\ub0C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications